This is of course a somewhat simplified picture of the progression, and omits the sports-science data generated from tracking devices and wearables and so on, but I think it is fairly representative of the increase in volumes of performance data that clubs could potentially take advantage of.

He adds:

Although some clubs are enthusiastic about the potentialities of data to inform decision-making, I have a suspicion that others are still rather uncertain, and while they may nominally claim to be “doing analytics” the real impact on their decision-making is rather limited.

Garry discusses analytics as decision-support as a four-stage process:

Information

Intelligence

Insight

Impact

Garry observes of this process:

The only reason data science exists as a function at all is to help the manager or coach do his job. The role of the analyst or data scientist is to support the footballing operations of the club by providing insights relevant to decision-making.

Lots to agree with here. I would add one thing. We can think of analytics as a "decision support system", but that's not all it is. We can also think of it as a strategy. I'd even argue that, unless it's a strategy, it will continue to struggle to have impact in football clubs. https://t.co/od0RGBEmZa

I think the intersection of Garry’s post and Chris’s insight sits well in the augmentation debate.

Melanie Cook (2017), for example, connects decision support and strategy in this slide:

Garry’s four steps in analytics can inform the long-term horizon of strategic thinking as an iterative process. I imagine that after a decade of involvement in football analytics, he is in a great position to offer inputs to those willing to consider longer performance cycles.